UM171 Expansion of Cord Blood Improves Donor Availability and HLA Matching For All Patients, Including Minorities
Bibliographic record
Abstract
Cord blood (CB) stem cell transplantation offers a greater tolerance to HLA mismatches compared to adult-derived stem cell transplants (i.e., bone marrow or peripheral blood stem cells). Indeed, 4/6 or 5/8 HLA-matched CB transplantations are regularly performed for patients lacking a matched unrelated donor. Unfortunately, most banked CB units contain a stem cell dose that is too small to treat adult patients, resulting in only 4% to 5% of available CB units offering an adequate cell dose for prompt engraftment for adult patients. Ex vivo stem cell expansion appears to be an attractive strategy to circumvent this cell dose issue, while also enabling the selection of better HLA-matched CB units. In this study, we retrospectively performed HLA matching simulations to assess how the minimal cell content requirements associated with UM171 CB expansion may improve usability of existing CB unit inventories and donor availability for patients of different races and ethnicities. We analyzed a dataset of 58,971 adults for whom a donor search was initiated through the National Marrow Donor Program Be The Match registry against 142,942 CB units from major U.S. public CB banks listed on the Be The Match registry. Our results show that by enabling selection of smaller CB units, UM171-expanded CB transplantation increases donor availability from 72% to 84% for all patients compared to single unmanipulated CB transplantation. Furthermore, the low cell dose criteria for UM171-expanded CB also increases donor availability compared to double CB transplantation, while enabling better HLA matching between donor and recipient. UM171 expanded CB appears particularly beneficial for racial and ethnic minority patients as CB availability increases from 53% to 78% for African Americans, from 66% to 85% for Hispanics, and from 68% to 84% for Asians and Pacific Islanders, compared to single unmanipulated CB transplantation. In addition, UM171 expansion dramatically improves usability of CB units currently in inventories, as only 4.3% and 0.6% of banked CBs have sufficient cell doses for a 70 kg and 100 kg patient, respectively. UM171 raises this proportion to 53.8% and 20.2%, respectively, making CB banks potentially more cost effective. In conclusion, UM171 expansion allows the use of smaller CB units while also improving access to transplantation for racial and ethnic minorities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".